The small subunit of Rubisco and its potential as an engineering target

Rubisco catalyses the first rate-limiting step in CO2 fixation and is responsible for the vast majority of organic carbon present in the biosphere. The function and regulation of Rubisco remain an important research topic and a longstanding engineering target to enhance the efficiency of photosynthesis for agriculture and green biotechnology. The most abundant form of Rubisco (Form I) consists of eight large and eight small subunits, and is found in all plants, algae, cyanobacteria, and most phototrophic and chemolithoautotrophic proteobacteria. Although the active sites of Rubisco are located on the large subunits, expression of the small subunit regulates the size of the Rubisco pool in plants and can influence the overall catalytic efficiency of the Rubisco complex. The small subunit is now receiving increasing attention as a potential engineering target to improve the performance of Rubisco. Here we review our current understanding of the role of the small subunit and our growing capacity to explore its potential to modulate Rubisco catalysis using engineering biology approaches

The Great British Liverwort Hunt – collecting wild accessions for molecular biology research while engaging the public

<p>During the lockdowns of the COVID-19 pandemic, outreach activities of universities were significantly perturbed. The Sainsbury Laboratory Cambridge University (SLCU) outreach project for the Cambridge festival in 2021 was therefore a fully online project, which asked people from across the mainland of the United Kingdom to send in plant samples of <i>Marchantia polymorpha</i>, and <i>Lunularia cruciata. </i>The samples were, upon arrival, established into axenic culture for use in research. Here, we deposit the names and locational data of the lines established in axenic culture for the wider use of the research community. Out of 76 samples received, 68 were successfully established in sterile tissue culture. This dataset also includes an analysis of the sex of the <i>M. polymorpha</i> accessions.</p&gt

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press